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Prediction of student's performance on the basis of his habits has been a very important research topic in academics. Studies also show that selection of the correct data set also plays a vital role in these predictions. In this paper we took data from different schools that contains students habits and their comments, analyzed it using Latent Semantic Analysis to get out semantics and the used Support Vector Machine to classify data into two classes, important for prediction and not important, finally we used Artificial Neural Networks to predict the grades of students regression was also used predict data coming from Support Vector Machine, while giving only the important data for prediction.

Given the growing impact of Science and Technology, particularly, information and communication technologies on every dimension of human life today, many parts of the world have been quicker in their response to the change for their own betterment. The wise realize that education lies at the centre of development in all fields. Therefore, these nations are now focused on upgrading all tiers of education to equip their youth with all essential skills to not only survive but lead their nations through 21st century. Pakistan is, unfortunately, one of the countries that lag behind. It has been, though, successful in upgradation of higher education. A lot needs to be done to bring school and college education up to the mark. Higher secondary education needs specific focus as this stage marks transitional phase of a child from adolescence to early adulthood at 16-18; hence significant changes in child's overall personality.

Due to wide variety of smart phones and capability of supporting heavy applications their demand is increasing day by day. Increase of computation capability and processing power Mobile cloud computing (MCC) becomes an emerging field. After cloud computing mobile cloud provide significant advantage and usage with reliability and portability. Challenges involved in mobile cloud computing are energy consumption, computation power and processing ability. Mobile cloud provides a way to use cloud resources on mobile but traditional models of smart phones does not support cloud so researchers introduce new models for the development of MCC. There are certain phases that still need improvement and this field attracts many researchers. Purpose of this chapter is to analyze and summarize the challenges involved in this field and work done so far.